Deployment options

CKEditor AI backend is available in two deployment modes: Cloud (SaaS) and On-premises. Both options provide the same core AI features – Chat, Quick Actions, Review, and Translate – with the on-premises version offering additional capabilities such as custom AI models and MCP support.

The Cloud (SaaS) deployment offers the fastest way to get started with CKEditor AI. The AI service is hosted and managed by CKEditor, so there is no server-side setup required on your end. You only need to provide a valid license key and configure the editor-side plugins as described in the integration guide.

For more information about the Cloud AI service, refer to the CKEditor AI Cloud Services documentation.

The on-premises deployment allows you to run the CKEditor AI service on your own infrastructure, including private cloud environments. The service is distributed as Docker images compatible with standard container runtimes.

On-premises deployment gives you full control over the AI service, including the ability to use custom AI models and providers, and to extend CKEditor AI with custom tools via MCP (Model Context Protocol).

For detailed setup instructions, requirements, and configuration, refer to the CKEditor AI On-Premises documentation.

To point the editor to your on-premises AI service, set the config.ai.serviceUrl property to the URL of your on-premises instance:

ClassicEditor
    .create( document.querySelector( '#editor' ), {
        licenseKey: '<YOUR_LICENSE_KEY>',

        ai: {
            serviceUrl: 'https://your-on-prem-host.com/v1',

            // ... Other AI configuration options.
        }

        // ... Other editor configuration.
    } )
    .then( /* ... */ )
    .catch( /* ... */ );

The on-premises version supports custom AI model providers, allowing you to use your own models hosted on services like Amazon Bedrock, Google Cloud, Microsoft Azure, or self-hosted solutions. Models configured on the server side will automatically appear in the editor’s model selector.

For configuration details, refer to the on-premises configuration guide.

The on-premises deployment supports the Model Context Protocol (MCP), which allows you to extend CKEditor AI with custom external tools. Learn more in the MCP support guide.